Sharing healthcare information with the public in electronic markets using blockchain: Three experimental studies and a machine learning analysis

Abstract

Abstract With the advent of digital markets such as cryptocurrency, the healthcare sector still lags behind regarding the richness of health data for public benefits. Due to the lack of public engagement and strict regulations, healthcare data is not available online. Blockchain technologies can address this problem; however, there is a lack of studies on mechanisms to explain how healthcare data can be shared from users’ side while taking care of privacy and security of information in online markets. Therefore, this paper proposes three main mediators to explain how healthcare data can be shared for public benefits in electronic markets. We use three experimental studies to provide empirical evidence for the proposed model, which contributes to the stimulus-organism-response (SOR) theory. A multimixed method, including structural equation modeling, regression analysis, and analysis of variances, is used to test the hypotheses. The results showed that three main mechanisms are peer-to-peer trade capability, healthcare improvement, and digital healthcare, which motivate users to engage in blockchain-based markets for sharing their healthcare information. Moreover, we used four machine learning algorithms to segment users and predict their behavior in trading their information, in which healthcare improvement was necessary to increase the positive impacts of peer-to-peer trade capability.